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/*! \file
    \brief Templates implementing warp-level matrix multiply-accumulate
   operations targeting Tensor Cores.
*/

#pragma once

#include "cutlass/cutlass.h"

#include "cutlass/array.h"
#include "cutlass/complex.h"
#include "cutlass/numeric_types.h"
#include "cutlass/matrix_shape.h"
#include "cutlass/functional.h"

#include "cutlass/arch/memory_sm75.h"
#include "cutlass/arch/mma_sm75.h"
#include "cutlass/arch/mma_sm80.h"

#include "cutlass/gemm/gemm.h"
#include "cutlass/gemm/warp/mma.h"

#include "cutlass/gemm/warp/mma_tensor_op_policy.h"
#include "cutlass/gemm/warp/mma_tensor_op.h"

#include "cutlass/gemm/warp/mma_tensor_op_tile_iterator.h"
#include "cutlass/gemm/warp/mma_tensor_op_tile_iterator_sm80.h"
#include "cutlass/gemm/warp/mma_complex_tensor_op_tile_iterator_sm80.h"

/////////////////////////////////////////////////////////////////////////////////////////////////

namespace cutlass {
namespace gemm {
namespace warp {

/////////////////////////////////////////////////////////////////////////////////////////////////

namespace detail {

template <
        /// Data type of real & imag members of complex numbers in the
        /// SourceFragment
        typename RealElement,
        /// Destination fragment required by the mma operation
        typename DestinationFragment,
        /// Source fragment holding complex<RealElement> elements
        typename SourceFragment,
        /// Number of mma operations performed
        typename MmaIterations,
        /// Shape of operand elements
        typename MmaOperandShape,
        /// Complex transform on A operand
        ComplexTransform Transform_,
        /// Operand A or Operand B
        Operand Operand_,
        /// Floating-point rounding style
        FloatRoundStyle Round_>
struct UnpackComplexConvertAndPackForMma;

// Partial specialization for OperandA and Congruous smem layout
template <typename RealElement, typename DestinationFragment,
          typename SourceFragment, typename MmaIterations,
          typename MmaOperandShape, ComplexTransform Transform_,
          FloatRoundStyle Round_>
struct UnpackComplexConvertAndPackForMma<
        RealElement, DestinationFragment, SourceFragment, MmaIterations,
        MmaOperandShape, Transform_, Operand::kA, Round_> {
    //
    // Type definitions
    //
    static Operand const kOperand = Operand::kA;
    static ComplexTransform const kTransform = Transform_;
    static FloatRoundStyle const kRound = Round_;

    // Data type of elements in the destination fragment
    using MmaElement = typename DestinationFragment::Element;

    // Numeric convertor MmaElement <= RealElement
    using Converter = NumericConverter<MmaElement, RealElement, kRound>;

    // Operand layout parameters
    using SourceFragmentLayout = layout::ColumnMajor;
    static int const kLdm = MmaIterations::kRow * MmaOperandShape::kRow;

    /// Ctor
    CUTLASS_DEVICE
    UnpackComplexConvertAndPackForMma() {}

    CUTLASS_DEVICE
    void operator()(DestinationFragment* dest, SourceFragment const& source) {
        Converter convert_op;
        SourceFragmentLayout layout(kLdm);

        CUTLASS_PRAGMA_UNROLL
        for (int i = 0; i < MmaIterations::kRow; i++) {
            int pos = 0;
            CUTLASS_PRAGMA_UNROLL
            for (int c = 0; c < MmaOperandShape::kColumn; c++) {
                CUTLASS_PRAGMA_UNROLL
                for (int r = 0; r < MmaOperandShape::kRow; r++) {
                    // Logical position of element in source fragment
                    int row = r + i * MmaOperandShape::kRow;
                    int col = c;

                    // Access complex<RealElement> and apply rounding on real
                    // and imag parts
                    MmaElement a = convert_op(
                            source[layout(MatrixCoord{row, col})].real());
                    MmaElement b = convert_op(
                            source[layout(MatrixCoord{row, col})].imag());

                    // Unpack rounded complex<MmaElement> and pack into
                    // DestinationFragment for mma operation
                    dest[i][pos] = a;
                    dest[i + MmaIterations::kRow][pos++] =
                            (kTransform == ComplexTransform::kConjugate ? -b
                                                                        : b);
                }
            }
        }
    }
};

// Partial specialization for OperandB and Congruous smem layout
template <typename RealElement, typename DestinationFragment,
          typename SourceFragment, typename MmaIterations,
          typename MmaOperandShape, ComplexTransform Transform_,
          FloatRoundStyle Round_>
struct UnpackComplexConvertAndPackForMma<
        RealElement, DestinationFragment, SourceFragment, MmaIterations,
        MmaOperandShape, Transform_, Operand::kB, Round_> {
    //
    // Type definitions
    //
    static Operand const kOperand = Operand::kB;
    static ComplexTransform const kTransform = Transform_;
    static FloatRoundStyle const kRound = Round_;

    // Data type of elements in the destination fragment
    using MmaElement = typename DestinationFragment::Element;

    // Numeric convertor MmaElement <= RealElement
    using Converter = NumericConverter<MmaElement, RealElement, kRound>;

    // Operand layout parameters
    using SourceFragmentLayout = layout::RowMajor;
    static int const kLdm = MmaIterations::kColumn * MmaOperandShape::kColumn;

    /// Ctor
    CUTLASS_DEVICE
    UnpackComplexConvertAndPackForMma() {}

    CUTLASS_HOST_DEVICE
    void operator()(DestinationFragment* dest, SourceFragment const& source) {
        Converter convert_op;
        SourceFragmentLayout layout(kLdm);

        CUTLASS_PRAGMA_UNROLL
        for (int i = 0; i < MmaIterations::kColumn; i++) {
            int pos = 0;
            CUTLASS_PRAGMA_UNROLL
            for (int c = 0; c < MmaOperandShape::kColumn; c++) {
                CUTLASS_PRAGMA_UNROLL
                for (int r = 0; r < MmaOperandShape::kRow; r++) {
                    // Logical position of element in source fragment
                    int row = r;
                    int col = c + i * MmaOperandShape::kColumn;

                    // Access complex<RealElement> apply rounding on real and
                    // imag parts
                    MmaElement a = convert_op(
                            source[layout(MatrixCoord{row, col})].real());
                    MmaElement b = convert_op(
                            source[layout(MatrixCoord{row, col})].imag());

                    // Unpack rounded complex<MmaElement> and pack into
                    // DestinationFragment for mma operation
                    dest[i][pos] = a;
                    dest[i + MmaIterations::kColumn][pos++] =
                            (kTransform == ComplexTransform::kConjugate ? -b
                                                                        : b);
                }
            }
        }
    }
};
}  // namespace detail

/////////////////////////////////////////////////////////////////////////////////////////////////

template <
        /// Size of the Gemm problem - concept: gemm::GemmShape<>
        typename Shape_,
        /// Data type of A elements
        typename RealElementA,
        /// Layout of A matrix (concept: MatrixLayout)
        typename LayoutA_,
        /// Data type of B elements
        typename RealElementB,
        /// Layout of B matrix (concept: MatrixLayout)
        typename LayoutB_,
        /// Element type of C matrix
        typename RealElementC,
        /// Layout of C matrix (concept: MatrixLayout)
        typename LayoutC_,
        /// Policy describing warp-level MmaTensorOp (concept: MmaTensorOp
        /// policy)
        typename Policy_,
        /// Complex transform on A operand
        ComplexTransform TransformA = ComplexTransform::kNone,
        /// Complex transform on B operand
        ComplexTransform TransformB = ComplexTransform::kNone,
        /// Used for partial specialization
        typename Enable = bool>
class MmaComplexTensorOp;

/////////////////////////////////////////////////////////////////////////////////////////////////

/// Partial specialization for complex*complex+complex => complex using
/// real-valued TensorOps
template <
        /// Size of the Gemm problem - concept: gemm::GemmShape<>
        typename Shape_,
        /// Data type of A elements
        typename RealElementA,
        /// Layout of A matrix (concept: MatrixLayout)
        typename LayoutA_,
        /// Data type of B elements
        typename RealElementB,
        /// Layout of B matrix (concept: MatrixLayout)
        typename LayoutB_,
        /// Element type of C matrix
        typename RealElementC,
        /// Layout of C matrix (concept: MatrixLayout)
        typename LayoutC_,
        /// Policy describing warp-level MmaTensorOp (concept: MmaTensorOp
        /// policy)
        typename Policy_,
        /// Complex transform on A operand
        ComplexTransform TransformA,
        /// Complex transform on B operand
        ComplexTransform TransformB,
        /// Used for partial specialization
        typename Enable>
class MmaComplexTensorOp<Shape_, complex<RealElementA>, LayoutA_,
                         complex<RealElementB>, LayoutB_, complex<RealElementC>,
                         LayoutC_, Policy_, TransformA, TransformB, Enable> {
public:
    /// Shape of warp-level matrix operation (concept: GemmShape)
    using Shape = Shape_;

    /// Data type of multiplicand A
    using ElementA = complex<RealElementA>;

    /// Layout of multiplicand A
    using LayoutA = LayoutA_;

    /// Data type of multiplicand B
    using ElementB = complex<RealElementB>;

    /// Layout of multiplicand B
    using LayoutB = LayoutB_;

    /// Data type of accumulator matrix C
    using ElementC = complex<RealElementC>;

    /// Layout of accumulator matrix C
    using LayoutC = LayoutC_;

    /// Shape of the warp in units of thread (concept: MmaLanePolicyTensorOp)
    using Policy = Policy_;

    /// Underlying matrix multiply operator (concept: arch::Mma)
    using ArchMmaOperator = typename Policy::Operator;

    /// Architecture tag from underlying instruction
    using ArchTag = typename ArchMmaOperator::ArchTag;

    /// Indicates class of matrix operator
    using OperatorClass = arch::OpClassTensorOp;

    /// Shape of underlying instruction
    using InstructionShape = typename ArchMmaOperator::Shape;

    /// Complex transform on A operand
    static ComplexTransform const kTransformA = TransformA;

    /// Complex transform on B operand
    static ComplexTransform const kTransformB = TransformB;

    /// Number of threads participating in warp-level matrix product
    static int const kThreadCount = 32;

public:
    /// Iterates over the A operand in memory
    using IteratorA = MmaTensorOpMultiplicandTileIterator<
            MatrixShape<Shape::kM, Shape::kK>, Operand::kA, ElementA, LayoutA,
            MatrixShape<ArchMmaOperator::Shape::kM, ArchMmaOperator::Shape::kK>,
            Policy::OpDelta::kRow, 32, 1>;

    /// Storage for A tile
    using FragmentA = typename IteratorA::Fragment;

    /// Storage for transformed A tile
    using TransformedFragmentA = FragmentA;

    /// Iterates over the B operand in memory
    using IteratorB = MmaTensorOpMultiplicandTileIterator<
            MatrixShape<Shape::kK, Shape::kN>, Operand::kB, ElementB, LayoutB,
            MatrixShape<ArchMmaOperator::Shape::kK, ArchMmaOperator::Shape::kN>,
            Policy::OpDelta::kColumn, 32, 1>;

    /// Storage for B tile
    using FragmentB = typename IteratorB::Fragment;

    /// Storage for transformed B tile
    using TransformedFragmentB = FragmentB;

    static_assert(
            !(Shape::kM % ArchMmaOperator::Shape::kM) &&
                    !(Shape::kN % ArchMmaOperator::Shape::kN),
            "Shape of warp-level Mma must be divisible by operator shape.");

    /// Number of mma operations performed
    using MmaIterations = MatrixShape<Shape::kM / ArchMmaOperator::Shape::kM,
                                      Shape::kN / ArchMmaOperator::Shape::kN>;

    /// Iterates over the C operand in memory
    using IteratorC = MmaTensorOpAccumulatorTileIterator<
            MatrixShape<Shape::kM, Shape::kN>, ElementC, LayoutC,
            typename ArchMmaOperator::Shape, typename Policy::OpDelta>;

    /// Storage for C tile, the accumulator. Note, regardless of multiplicand
    /// type, this storage arrangement is to be considered 'planar complex' in
    /// the sense that all real-valued parts are stored consecutively followed
    /// by all imaginary parts. This matches the structure of Tensor Cores which
    /// are always real-valued matrix multiplies.
    using FragmentC = typename IteratorC::Fragment;

    static_assert(FragmentC::kElements ==
                          2 * MmaIterations::kCount *
                                  ArchMmaOperator::FragmentC::kElements,
                  "Unexpected planar complex fragment length.");

private:
    //
    // Data members
    //

    /// Underlying real-valued matrix multiply operator (concept: arch::Mma)
    ArchMmaOperator mma;

public:
    //
    // Methods
    //

    /// Ctor
    CUTLASS_DEVICE
    MmaComplexTensorOp() {}

    /// Performs a warp-level matrix multiply-accumulate operation
    CUTLASS_DEVICE
    void operator()(FragmentC& D, FragmentA const& A, FragmentB const& B,
                    FragmentC const& C) const {
        // Alias types for underlying real-valued matrix multiply operator
        using MmaOperandA = typename ArchMmaOperator::FragmentA;
        using MmaOperandB = typename ArchMmaOperator::FragmentB;
        using MmaOperandC = typename ArchMmaOperator::FragmentC;

        static_assert(MmaOperandA::kElements == 1,
                      "This implementation only supports math instructions in "
                      "which exactly one element is needed for the A operand."
                      "We can geneneralize later.");

        static_assert(MmaOperandB::kElements == 1,
                      "This implementation only supports math instructions in "
                      "which exactly one element is needed for the B operand."
                      "We can geneneralize later.");

        D = C;

        CUTLASS_PRAGMA_UNROLL
        for (int m = 0; m < MmaIterations::kRow; ++m) {
            // mma(accum.real(), a.real(), b.real(), accum.real());
            CUTLASS_PRAGMA_UNROLL
            for (int n = 0; n < MmaIterations::kColumn; ++n) {
                // Pack operands together. This may result in actual MOVs
                MmaOperandA operand_A;
                MmaOperandB operand_B;

                operand_A[0] = A[m].real();
                operand_B[0] = B[n].real();

                // Real-valued accumulator part
                MmaOperandC* accum = reinterpret_cast<MmaOperandC*>(&D) +
                                     (m + n * MmaIterations::kRow);

                mma(*accum, operand_A, operand_B, *accum);
            }

            // mma(accum.imag(), a.real(), b.imag(), accum.imag());
            CUTLASS_PRAGMA_UNROLL
            for (int n = MmaIterations::kColumn - 1; n >= 0; --n) {
                // Pack operands together. This may result in actual MOVs
                MmaOperandA operand_A;
                MmaOperandB operand_B;

                operand_A[0] = A[m].real();
                operand_B[0] = (kTransformB == ComplexTransform::kConjugate
                                        ? -B[n].imag()
                                        : B[n].imag());

                // Complex-valued accumulator part
                MmaOperandC* accum = reinterpret_cast<MmaOperandC*>(&D) +
                                     (m + n * MmaIterations::kRow) +
                                     MmaIterations::kCount;

                mma(*accum, operand_A, operand_B, *accum);
            }

            // mma(accum.real(), -a.imag(), b.imag(), accum.real())
            CUTLASS_PRAGMA_UNROLL
            for (int n = 0; n < MmaIterations::kColumn; ++n) {
                // Pack operands together. This may result in actual MOVs
                MmaOperandA operand_A;
                MmaOperandB operand_B;

                // A imaginary part is intentionally negated
                operand_A[0] = (kTransformA == ComplexTransform::kConjugate
                                        ? A[m].imag()
                                        : -A[m].imag());
                operand_B[0] = (kTransformB == ComplexTransform::kConjugate
                                        ? -B[n].imag()
                                        : B[n].imag());

                // Real-valued accumulator part
                MmaOperandC* accum = reinterpret_cast<MmaOperandC*>(&D) +
                                     (m + n * MmaIterations::kRow);

                mma(*accum, operand_A, operand_B, *accum);
            }

            // mma(accum.imag(), a.imag(), b.real(), accum.imag())
            CUTLASS_PRAGMA_UNROLL
            for (int n = MmaIterations::kColumn - 1; n >= 0; --n) {
                // Pack operands together. This may result in actual MOVs
                MmaOperandA operand_A;
                MmaOperandB operand_B;

                operand_A[0] = (kTransformA == ComplexTransform::kConjugate
                                        ? -A[m].imag()
                                        : A[m].imag());
                operand_B[0] = B[n].real();

                // Complex-valued accumulator part
                MmaOperandC* accum = reinterpret_cast<MmaOperandC*>(&D) +
                                     (m + n * MmaIterations::kRow) +
                                     MmaIterations::kCount;

                mma(*accum, operand_A, operand_B, *accum);
            }
        }
    }

    /// Transform the mma operands to the required types
    CUTLASS_DEVICE
    void transform(TransformedFragmentA& dst_A, TransformedFragmentB& dst_B,
                   FragmentA const& A, FragmentB const& B) const {
        // TODO: Implement this
        dst_A = A;
        dst_B = B;
    }
};

/////////////////////////////////////////////////////////////////////////////////////////////////

/// Partial specialization for complex*complex+complex => complex:
//  Operands data type: complex<float>
//  Rounding: float -> tfloat32_t (round half_ulp_truncate nearest)
//  Math instruction: MMA.1688.F32.TF32
//  Output data type: complex<float>
//
/////////////////////////////////////////////////////////////////////////////////////////////////
template <
        /// Size of the Gemm problem - concept: gemm::GemmShape<>
        typename Shape_,
        /// Layout of A matrix (concept: MatrixLayout)
        typename LayoutA_,
        /// Layout of B matrix (concept: MatrixLayout)
        typename LayoutB_,
        /// Layout of C matrix (concept: MatrixLayout)
        typename LayoutC_,
        /// Policy describing warp-level MmaTensorOp (concept: MmaTensorOp
        /// policy)
        typename Policy_,
        /// Complex transform on A operand
        ComplexTransform TransformA,
        /// Complex transform on B operand
        ComplexTransform TransformB,
        /// Used for partial specialization
        typename Enable>
class MmaComplexTensorOp<Shape_, complex<float>, LayoutA_, complex<float>,
                         LayoutB_, complex<float>, LayoutC_, Policy_,
                         TransformA, TransformB, Enable> {
public:
    /// Shape of warp-level matrix operation (concept: GemmShape)
    using Shape = Shape_;

    /// Data type of members of complex multiplicand A
    using RealElementA = float;

    /// Data type of multiplicand A
    using ElementA = complex<RealElementA>;

    /// Layout of multiplicand A
    using LayoutA = LayoutA_;

    /// Data type of members of complex multiplicand B
    using RealElementB = float;

    /// Data type of multiplicand B
    using ElementB = complex<RealElementB>;

    /// Layout of multiplicand B
    using LayoutB = LayoutB_;

    /// Data type of members of complex accumulator matrix C
    using RealElementC = float;

    /// Data type of accumulator matrix C
    using ElementC = complex<RealElementC>;

    /// Layout of accumulator matrix C
    using LayoutC = LayoutC_;

    /// Shape of the warp in units of thread (concept: MmaLanePolicySimt)
    using Policy = Policy_;

    /// Underlying matrix multiply operator (concept: arch::Mma)
    using ArchMmaOperator = typename Policy::Operator;

    /// Shape of underlying instruction
    using InstructionShape = typename ArchMmaOperator::Shape;

    /// Underlying arch tag
    using ArchTag = typename ArchMmaOperator::ArchTag;

    /// Indicates class of matrix operator
    using OperatorClass = arch::OpClassTensorOp;

    /// Complex transform on A operand
    static ComplexTransform const kTransformA = TransformA;

    /// Complex transform on B operand
    static ComplexTransform const kTransformB = TransformB;

    /// Number of threads participating in warp-level matrix product
    static int const kThreadCount = 32;

public:
    /// Iterates over the A operand in memory
    using IteratorA = MmaTensorOpMultiplicandTileIterator<
            MatrixShape<Shape::kM, Shape::kK>, Operand::kA, ElementA, LayoutA,
            MatrixShape<ArchMmaOperator::Shape::kM, ArchMmaOperator::Shape::kK>,
            Policy::OpDelta::kRow, 32, 1>;

    /// Storage for A tile
    using FragmentA = typename IteratorA::Fragment;

    /// Storage for transformed A tile
    using TransformedFragmentA =
            Array<typename ArchMmaOperator::ElementA, FragmentA::kElements * 2>;

    /// Iterates over the B operand in memory
    using IteratorB = MmaTensorOpMultiplicandTileIterator<
            MatrixShape<Shape::kK, Shape::kN>, Operand::kB, ElementB, LayoutB,
            MatrixShape<ArchMmaOperator::Shape::kK, ArchMmaOperator::Shape::kN>,
            Policy::OpDelta::kColumn, 32, 1>;

    /// Storage for B tile
    using FragmentB = typename IteratorB::Fragment;

    /// Storage for transformed B tile
    using TransformedFragmentB =
            Array<typename ArchMmaOperator::ElementB, FragmentB::kElements * 2>;

    static_assert(
            !(Shape::kM % ArchMmaOperator::Shape::kM) &&
                    !(Shape::kN % ArchMmaOperator::Shape::kN),
            "Shape of warp-level Mma must be divisible by operator shape.");

    /// Number of complex products operations performed (one complex product
    /// needs four mma instructions)
    using MmaIterations = MatrixShape<Shape::kM / ArchMmaOperator::Shape::kM,
                                      Shape::kN / ArchMmaOperator::Shape::kN>;

    /// Iterates over the C operand in memory
    using IteratorC = MmaTensorOpAccumulatorTileIterator<
            MatrixShape<Shape::kM, Shape::kN>, ElementC, LayoutC,
            typename ArchMmaOperator::Shape, typename Policy::OpDelta>;

    /// Storage for C tile, the accumulator. Note, regardless of multiplicand
    /// type, this storage arrangement is to be considered 'planar complex' in
    /// the sense that all real-valued parts are stored consecutively followed
    /// by all imaginary parts. This matches the structure of Tensor Cores which
    /// are always real-valued matrix multiplies.
    using FragmentC = typename IteratorC::Fragment;

private:
    //
    // Data members
    //

    /// Underlying real-valued matrix multiply operator (concept: arch::Mma)
    ArchMmaOperator mma;

public:
    //
    // Methods
    //

    /// Ctor
    CUTLASS_DEVICE
    MmaComplexTensorOp() {}

    /// Performs a warp-level matrix multiply-accumulate operation
    CUTLASS_DEVICE
    void operator()(FragmentC& D, TransformedFragmentA const& A,
                    TransformedFragmentB const& B, FragmentC const& C) const {
        // Alias types for underlying real-valued matrix multiply operator
        using InstMmaOperandA = typename ArchMmaOperator::FragmentA;
        using InstMmaOperandB = typename ArchMmaOperator::FragmentB;
        using MmaOperandC = typename ArchMmaOperator::FragmentC;

        static_assert(platform::is_same<cutlass::gemm::GemmShape<16, 8, 8>,
                                        typename ArchMmaOperator::Shape>::value,
                      "This implementation only supports MMA.1688 math "
                      "instructions.");

        static_assert(InstMmaOperandA::kElements == 4,
                      "This implementation only supports math instructions in "
                      "which exactly four element is needed for the A operand."
                      "We can geneneralize later.");

        static_assert(InstMmaOperandB::kElements == 2,
                      "This implementation only supports math instructions in "
                      "which exactly two element is needed for the B operand."
                      "We can geneneralize later.");

        // Instruction Operands A & B holding real part followed by imaginary
        // part for mma operations
        InstMmaOperandA const* operand_A =
                reinterpret_cast<InstMmaOperandA const*>(&A);
        InstMmaOperandB const* operand_B =
                reinterpret_cast<InstMmaOperandB const*>(&B);

        //
        // Accumulate in place
        //
        D = C;

        CUTLASS_PRAGMA_UNROLL
        for (int m = 0; m < MmaIterations::kRow; ++m) {
            // mma(accum.real(), a.real(), b.real(), accum.real());
            CUTLASS_PRAGMA_UNROLL
            for (int n = 0; n < MmaIterations::kColumn; ++n) {
                // Real-valued accumulator part
                MmaOperandC* accum = reinterpret_cast<MmaOperandC*>(&D) +
                                     (m + n * MmaIterations::kRow);

                mma(*accum, operand_A[m], operand_B[n], *accum);
            }

            // mma(accum.imag(), a.real(), b.imag(), accum.imag());
            CUTLASS_PRAGMA_UNROLL
            for (int n = MmaIterations::kColumn - 1; n >= 0; --n) {
                // Complex-valued accumulator part
                MmaOperandC* accum = reinterpret_cast<MmaOperandC*>(&D) +
                                     (m + n * MmaIterations::kRow) +
                                     MmaIterations::kCount;

                mma(*accum, operand_A[m], operand_B[n + MmaIterations::kColumn],
                    *accum);
            }

            // mma(accum.real(), a.imag(), -b.imag(), accum.real())
            CUTLASS_PRAGMA_UNROLL
            for (int n = 0; n < MmaIterations::kColumn; ++n) {
                // negate OperandB to accumulate  -(a.imag()*b.imag())
                // negating OperandB emits less instrucitons than negating
                // OperandA as OperandB has less elements
                negate<InstMmaOperandB> negate_op;

                // Real-valued accumulator part
                MmaOperandC* accum = reinterpret_cast<MmaOperandC*>(&D) +
                                     (m + n * MmaIterations::kRow);

                mma(*accum, operand_A[m + MmaIterations::kRow],
                    negate_op(operand_B[n + MmaIterations::kColumn]), *accum);
            }

            // mma(accum.imag(), a.imag(), b.real(), accum.imag())
            CUTLASS_PRAGMA_UNROLL
            for (int n = MmaIterations::kColumn - 1; n >= 0; --n) {
                // Complex-valued accumulator part
                MmaOperandC* accum = reinterpret_cast<MmaOperandC*>(&D) +
                                     (m + n * MmaIterations::kRow) +
                                     MmaIterations::kCount;

                mma(*accum, operand_A[m + MmaIterations::kRow], operand_B[n],
                    *accum);
            }
        }
    }

    /// Transform the mma operands to the required types
    CUTLASS_DEVICE
    void transform(TransformedFragmentA& dst_A, TransformedFragmentB& dst_B,
                   FragmentA const& A, FragmentB const& B) const {
        // Alias types for underlying real-valued matrix multiply operator
        using InstMmaOperandA = typename ArchMmaOperator::FragmentA;
        using InstMmaOperandB = typename ArchMmaOperator::FragmentB;

        //
        // Define conversions from source type to instruction operands' type
        //

        FloatRoundStyle const kRoundA =
                FloatRoundStyle::round_half_ulp_trunc_dntz;
        FloatRoundStyle const kRoundB =
                FloatRoundStyle::round_half_ulp_trunc_dntz;

        detail::UnpackComplexConvertAndPackForMma<
                RealElementA, InstMmaOperandA, FragmentA, MmaIterations,
                MatrixShape<2, 2>, kTransformA, Operand::kA, kRoundA>
                convert_A;

        detail::UnpackComplexConvertAndPackForMma<
                RealElementB, InstMmaOperandB, FragmentB, MmaIterations,
                MatrixShape<2, 1>, kTransformB, Operand::kB, kRoundB>
                convert_B;

        // Convert Fragment[A|B] holding complex<RealElement[A|B]> to
        // InstMmaOperand[A|B] holding InstMmaOperand[A|B]::Element
        convert_A(reinterpret_cast<InstMmaOperandA*>(&dst_A), A);
        convert_B(reinterpret_cast<InstMmaOperandB*>(&dst_B), B);
    }
};

/////////////////////////////////////////////////////////////////////////////////////////////////

// TODO - partial specializations of real*complex and complex*real

/////////////////////////////////////////////////////////////////////////////////////////////////

}  // namespace warp
}  // namespace gemm
}  // namespace cutlass

/////////////////////////////////////////////////////////////////////////////////////////////////
